如何有效地将NaN放入熊猫数据帧中？

import pandas as pd
import numpy as np

# 创建一个空的DataFrame
df = pd.DataFrame()

# 添加包含NaN的列
df['A'] = [1, 2, np.nan, 4]

print(df)

import pandas as pd

# 创建一个空的DataFrame
df = pd.DataFrame()

# 添加包含NaN的列
df['A'] = [1, 2, pd.NA, 4]

print(df)

import pandas as pd
import numpy as np

# 创建一个包含缺失值的数组
data = [1, 2, np.nan, 4]

# 将数组转换为DataFrame
df = pd.DataFrame(data, columns=['A'])

print(df)

# 检查整个DataFrame中是否存在NaN
has_nan = df.isnull().values.any()
print(has_nan)

# 检查特定列中是否存在NaN
has_nan_in_column_A = df['A'].isnull().any()
print(has_nan_in_column_A)

# 删除包含NaN的行
df_cleaned = df.dropna()

# 填充NaN
df_filled = df.fillna(0)  # 用0填充NaN
df_filled = df.fillna(method='ffill')  # 用前一个值填充NaN
df_filled = df.fillna(method='bfill')  # 用后一个值填充NaN